Detection of murine leukemia virus in the Epstein-Barr virus-positive human B-cell line JY, using a computational RNA-Seq-based exogenous agent detection pipeline, PARSES

Abstract

Many cell lines commonly used for biological studies have been found to harbor exogenous agents such as the human tumor viruses Epstein-Barr virus (EBV) and human papillomavirus. Nevertheless, broad-based, unbiased approaches to globally assess the presence of ectopic organisms within cell model systems have not previously been available. We reasoned that high-throughput sequencing should provide unparalleled insights into the microbiomes of tissue culture cell systems. Here we have used our RNA-seq analysis pipeline, PARSES (Pipeline for Analysis of RNA-Seq Exogenous Sequences), to investigate the presence of ectopic organisms within two EBV-positive B-cell lines commonly used by EBV researchers. Sequencing data sets from both the Akata and JY B-cell lines were found to contain reads for EBV, and the JY data set was found to also contain reads from the murine leukemia virus (MuLV). Further investigation revealed that MuLV transcription in JY cells is highly active. We also identified a number of MuLV alternative splicing events, and we uncovered evidence of APOBEC3G (apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like 3G)-dependent DNA editing. Finally, reverse transcription-PCR analysis showed the presence of MuLV in three other human B-cell lines (DG75, Ramos, and P3HR1 Cl.13) commonly used by investigators in the Epstein-Barr virus field. We believe that a thorough examination of tissue culture microbiomes using RNA-seq/PARSES-like approaches is critical for the appropriate utilization of these systems in biological studies.

Fig 1

PARSES analysis of RNA-seq data from the EBV-positive cell lines Akata and JY. (A) Schematic diagram showing essential components of PARSES pipeline. One gigabyte of RNA-seq read data from Akata (B) and JY (C) cells was analyzed using PARSES. The resulting virome data were displayed using MEGAN 4. Both data sets show the presence of EBV as well as ϕX174 (used as a spike-in sequencing control).

Fig 2

JY MuLV genome sequence analysis. (A) Alignment of JY RNA-seq reads to N417 and JY MuLV genomes. All mismatches, a small deletion, and a small insertion (Ins) observed from the alignment to the N417 genome are shown in the top eight panels. Coverage data for alignments to the N417 and JY genomes are shown in the lower two panels. The light red shaded region at the right side of the env feature represents the longer conserved env extension in the N417 genome which is partially penetrant in the JY data. (B) JY MuLV is highly related to the N417 strain of MuLV. Alignments were performed using the MegAlign program (DNAstar Inc., Madison, WI). LTR, long terminal repeat.

Fig 3

MuLV transcript quantification. (A) Total read counts at most highly represented genomic loci. Read counts for MuLV include all reads mapping to the viral genome. Read counts for cellular genes include all reads mapping to the respective gene exons. (B) RPKMs are shown for 3 of the top 10 expressed loci (rightward three bars) and two genes with expression near the median of all expressed genes (leftward three bars and inset). Median expression was calculated on the basis of all genes with an expression level of greater than 1 RPKM.

Fig 4

Most abundant MuLV splicing events detected in JY cells. TopHat-predicted rightward junctions with greater than 15 reads per junction are displayed. Junctions in green shading were validated by RT-PCR, followed by cloning and Sanger sequencing. Junction 8 and junction 6 plus junction 128 represent possible splicing events leading to expression of the env gene. Junction 225 represents an in-frame splicing event predicted to give rise to a Gag-Pol-Pro polypeptide lacking functional regions of the reverse transcriptase. The number of reads spanning validated junctions is shown in parentheses.

Fig 5

Partially penetrant G-to-A changes present in greater than 5% of reads. Nucleotide position is plotted on the x axis. UTR, untranslated region.

Fig 6

Detection of MuLV in other laboratory cell lines. (A) Nonquantitative RT-PCR detects MuLV-related virus in several laboratory cell lines. Lane M, molecular size marker; lane NTC, no-template control. (B) Quantitative RT-PCR analysis of a larger panel of B-cell lines shows the presence of MuLV-related virus in DG75, Ramos, P3HR1 Cl.13, and JY cells.